HCC-Small: Investigating and Supporting the Iterative and Exploratory Process of Applying Statistical Machine Learning

HCC-Small：调查和支持应用统计机器学习的迭代和探索过程

• 批准号: 0812590
• 负责人: James Fogarty
• 金额: $ 44.95万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0812590&HistoricalAwards=false
• 关键词: HCC; Small; Investigating; Supporting; Iterative

Software engineering emerged out of a need to better address the real-world development of software, transforming the practice of software development from an art, into a craft, and eventually into an engineering discipline. In contrast, the effective application of statistical machine learning algorithms and techniques currently remains an art, based primarily in expert intuition and experience. This project is an integrated program of research and education targeting researcher, student, and practitioner application of statistical machine learning algorithms and techniques as tools for software development. The research focuses on the design of human-centered computing through the investigation of the needs of people applying statistical machine learning as a tool for software development, the creation of new methods and tools supporting the development and deployment of applications that use statistical machine learning, and the evaluation of these new methods and tools in supporting the complex and exploratory task of applying statistical machine learning. There are two primary foci in a new proposed toolset: explicit support for history and experimentation in an iterative and exploratory process and new opportunities for mixed-initiative tools to aid that process. By examining the application of statistical machine learning as a craft, this research enables the potential broad impact of statistical machine learning as a tool for software development in human-centered computing research and applications.

软件工程的出现是为了更好地解决软件的现实世界开发的需要，将软件开发的实践从一门艺术转变为一门手艺，并最终成为一门工程学科。相比之下，统计机器学习算法和技术的有效应用目前仍然是一门艺术，主要基于专家的直觉和经验。该项目是一个研究和教育的综合计划，目标是研究人员，学生和从业人员应用统计机器学习算法和技术作为软件开发工具。该研究的重点是以人为本的计算设计，通过调查应用统计机器学习作为软件开发工具的人们的需求，创建支持使用统计机器学习的应用程序的开发和部署的新方法和工具，以及评估这些新方法和工具在支持应用统计机器学习的复杂和探索性任务方面的作用。在新提出的工具集中有两个主要焦点：明确支持历史和实验，在一个迭代和探索的过程和新的机会，混合倡议的工具，以帮助这一进程。通过研究统计机器学习作为一种工艺的应用，这项研究使统计机器学习作为以人为中心的计算研究和应用中的软件开发工具的潜在广泛影响成为可能。